Three Approaches To Data Analysis

In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.

Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999

This four-volume major work collates and contextualises key papers on the use of case study in education. The collection brings together methodological publications and publications which provide exemplars of case study. The methodological material provides both critical analyses of case study and those which champion its use, offering at the same time a chronological map of the development of case study from its earliest uses to today. Framed by an introductory passage in each volume which seeks to provide a synopsis of the methodological discussion and a commentary on the exemplary material, this set provides for serious students in education original source material to appraise the method together with exemplary sample material to help them plan and organize their case studies. Volume One: Methodological issues around the use of case studies in social science Volume Two: Methodological issues around the use of case studies in education Volume Three: The case study in practice - general issues and specific examples Volume Four: Examples of case studies in education

Nursing Research Using Data Analysis: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for novice researchers and specialists seeking to develop or expand their competency, health institution research divisions, in-service educators and students, and graduate nursing educators and students.

Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.

"Completely revised With timely content and state-of-the-art research undertaken by Canadian nurse researchers, the Third Edition of this trusted resource provides the guidance you need to effectively critique every aspect of nursing research and apply the results to clinical practice. Canadian Essentials of Nursing Research uses clear, straightforward language and a "user-friendly" presentation to help you understand, retain, and apply fundamental concepts with ease." --Book Jacket.

This graduate level nursing research textbook continues the expansion of coverage on qualitative research, including important issues for specific qualitative traditions such as grounded theory, phenomenology and ethnography. Developing solid evidence for practice will be emphasized throughout the text, and important evaluative concepts like reliability, validity, and trustworthiness will be introduced. Other new features include stronger international content (with an emphasis on Canadian and Australian research), inclusion of “tips” in boxes located in appropriate places throughout the chapters, and the use of summary bullet points. This edition will now offer a free Connection Website, connection.LWW.com/go/polit.